There exists a great deal of knowledge, experience, data and operational experience in the prior art surrounding the field generally known as electronic payment transaction processing and the corresponding systems and methods that operate the various electronic payment networks. Exemplary payment transactions systems include well-known brands such as Visa, MasterCard, Discover, American Express (a.k.a Amex), and other networks such as the Automated Clearinghouse (ACH) system operated by the National Automated Clearinghouse Association (NACHA), paper check and check image processing system, coupon redemption systems, customer loyalty or reward (aka ‘points’) systems and the like. Traditionally, these systems are intended to efficiently and securely facilitate the transfer of monetary value from a buyer to a seller who provided a product, good, or service to the buyer for the agreed upon value amount. Typically the buyer and seller (or customer, business, or other entity relationship) have utilized a variety of electronic transaction processing methods, electronic messages, electronic data formats, machine formats and the like to accomplish the value or payment transfer and then typically they utilize a second separate system to deliver the physical or digital item, good, or service to the buyer. Thus, these electronic payment transaction processing systems do not facilitate the transfer of knowledge about the customer to the buyer and instead focus on monetary accuracy, speed, reliability, and being a guaranteed source of known good funds.
However, to facilitate future sales or to enhance existing or future transactions between a buyer and the seller, it would be advantageous for the seller to know how to reach customers via a known good transaction information channel which exists outside of the payment or value transfer systems. Historically, sellers reached out or communicated to prospective customers via advertising and marketing systems and methods which are separate from and distinct from the payment processing channels or systems. Thus to drive sales and increase business, a seller or company must know how to “reach” their existing customers or utilize broad reach mass market advertising and sales methods with unsure or unproven results in terms of effectiveness in reaching the desired or targeted customer. This fact may be mitigated when companies or sellers utilize channels which are based on personally identifiable data provided by their existing or previous customers during a prior transaction. Systems which are based on voluntary, personal or identifiable customer data or knowledge that was gathered provided or agreed to by a customer during or after previous transactions are generally considered or known as rewards programs or loyalty programs. These reward programs are seen as valuable by customers who wish to make repeat purchases from the same seller or company and historically companies utilize these systems to track existing customer behavior, patterns, preferences and general statistical knowledge about their customers for use in planning future sales, marketing or various other business methods, goals or objectives. Even with these existing “loyalty or reward” type systems and methods, sellers or companies who wish to reach their previous customers must depend on personally identifiable data which has provided by the customer under a voluntary or “opt-in” process. Typically this information is provided by their customer during previous sales transactions which may or not be provided to the company or seller during the payment transaction processing method used at the time of their prior purchase. Disadvantageously, “loyalty or reward” type systems and methods require voluntary participation from previous customers and are not able to target new customers and those customers who “opt-out.”
Based on the foregoing, it would be advantageous to have a new type of engagement channel which could enhance the type, level and amount of communication and data exchange between customers/buyers and sellers/companies. Such a new type of channel would overcome the unsure or unproven results associated with broad reach mass market advertising and sales methods and the limited audience reach associated with “loyalty or reward” type systems and methods. Designing and developing a new engagement channel or system requires overcoming the errors, limitations or weaknesses of prior art, systems or methods which may have attempted similar results but failed to achieve them given their inability to deal with the unpredictable and widely varying set of data elements that may be produced by the various transaction processing systems as well as the location of these systems within the payment transaction processing marketplace or the scope or reach of these systems not being universal such as the present invention.
There are existing business methods, patents or applications that are known to those in the industry which attempt to do similar sounding but different aspects of processing, matching, inspecting, sorting, organizing data and the like from customer and company transaction or payment data. Some of the more notable of these prior art inventions will be described herein in order to clearly differentiate the current invention from their similar sounding names, concepts or ideas. None of these existing or known systems or methods should be inferred to teach, suggest or make obvious any of the current inventions novel or key aspects, ideas and inventive steps or elements.
US Patent Publication Number 2011/0022628, “Matching Merchant Names from Transaction Data”, application Ser. No. 12/900,261 by Kramer. The Kramer reference describes a computer system process to determine a “matched merchant name” from transaction data. This method requires and depends on a previously “processed merchant name” from a “retrieved merchant name” in order to match the processed merchant name to one of a collection of “standard merchant names”. Further, it declares that “at least one character of the retrieved merchant name may be altered to obtain the processed merchant name”—for example characters may be deleted or ignored to make a match. Some of the key deficiencies of the Kramer reference include:    1. The system described by Kramer relies on the fact that the merchant name retrieved from the payment data is used to derive the “standard merchant name”, which is then associated with indicia information. For instance, the Kramer reference could derive “ABC” from the merchant name of “ABC Store 100” which was retrieved from a set of transaction data because the merchant name retrieved from the transaction data includes a minimum match on “ABC”. However, this prior art would not be able to find a match or derive a standard merchant name if the merchant name used in the transaction data was “12345” since it does not have any portion of ABC in it.    2. The Kramer reference does not contemplate or include the ability to identify specific merchant locations from transaction data but simply the broadest level of “merchant” name. In fact, the Kramer reference specifically disregards location specific information, such as the store number, in order to derive a “standard merchant name”.    3. The Kramer reference does not contemplate or include the ability to identify specific devices used during transactions.    4. The Kramer reference does not contemplate or include the ability to associate categories with retrieved merchant name.    5. The Kramer reference does not contemplate or include the ability to include Transaction Data or Customer receipt data as part of the indicia.    6. The Kramer reference does not contemplate or include the ability to use an actual payment (i.e., Company Payment) to link a Merchant Name and other data with a specific Company.    7. The Kramer reference does not contemplate or include the ability to use Merchant Data from an Acquirer to identify and link Merchant Name with a Company.    8. The Kramer reference does not contemplate or include the ability to link Product Data, such as user manuals and warranties, based on Product purchases as part of a Transaction.    9. The Kramer reference does not contemplate or include the ability to define and process Rewards.    10. The Kramer reference does not contemplate or include the ability to validate and process a Coupon or other type of marketing offer.    11. The Kramer reference does not contemplate or include the ability to enrich indicia information.    12. The Kramer reference does not contemplate or include the ability to share indicia information outside the system.    13. The Kramer reference has a limited operating position within the transaction or payment eco-system and thus cannot operate at the scope or level of the present inventions. For example, the system described in Kramer does not contemplate operating on data from outside of a single card issuer operational or transactional perspective. That is, the scope of its claims limit the matching to data from a single card issuer and it cannot operate across issuers, acquirers, merchants, third party reward systems and the like, thus its scope and applicability are limited and cannot operate in a manner or at a level as needed.
Additionally, another conventional solution includes U.S. Pat. No. 7,908,170 by Asmar titled “System and Method for Facilitating Commercial Transactions” which provides a system that “provides vital marketing information to participating merchants and purchasing records to customers while offering the most efficient and effective system to deliver the best terms and conditions for the products and services requested by customers”. Note that this system does not contemplate matching Merchant Names or IDs to transaction data nor does it provide the other embodiments or features as it depends on real-time approval of a transaction at checkout. Another element of the prior art is US2012/0084135 (application Ser. No. 12/896,442) by Nissan titled “System and Method for Tracking Transaction Records in a Network” which provides a system for “processing a transaction record of a transaction between a merchant and a user”. This system updates Customer records based on specified and well defined terminals which enable the processing of transaction sales data by Merchants who participate in the “network” provided by this invention. Note that this method again requires real-time participation in the “checkout” transaction by specified hardware or terminals that connect to a proprietary network. This method cannot work with data generated outside of the network nor can it work with data after the fact as may be enabled by a Customer statement provider. Finally, there is US2008/0103912 (application Ser. No. 11/924,323) by Naccache which describes a “Method of Providing Transaction Data, Terminal, Transaction Method, Method of Enhancing Bank Statements, Server, Signals and Computer Program Products Corresponding Thereto” which as the name implies requires a specialized terminal or device to generate enhanced data for statements such as pictures or images. The method provides “for each transaction a statement line containing at least one reference” for a specified transaction with the image being provided of the merchant store exterior, location and or item purchased. This system cannot work with Transaction data generated by outside systems and methods nor can it provide the other benefits.
As it can be seen by those of ordinary skill in the art, these existing systems, methods and well known prior art do not utilize the unique method to identify Customers based on known Company identifiers based on transaction data. Additionally, these existing systems cannot provide the same level of interaction with customers whether they are known or unknown and they cannot create the interactive and real-time Customer interaction or engagement channel.